Position PaperAdvancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria
Introduction
In 2007, the International Working Group (IWG) for New Research Criteria for the Diagnosis of Alzheimer's Disease (AD) provided a new conceptual framework that proposes to anchor the diagnosis of AD on the presence of biomarkers.1 A goal of these diagnostic criteria, and of the subsequent National Institute on Aging–Alzheimer's Association (NIA–AA) criteria,2 has been to expand coverage of the full range of disease stages, from the asymptomatic through the most severe stages of dementia. Potentially, their most important practical application is to allow earlier intervention in the prodromal stages of the disease and to facilitate research studies into secondary prevention of AD in the preclinical states. As we learn more through the research application of these criteria, common ground is being found for the eventual development of a universal set of criteria that truly captures the essence of AD.
In parallel, research into biomarkers has helped to clarify the potential value of each marker in the diagnosis of AD. Data highlight the value of cued recall measures for the assessment of episodic memory impairment; the relevance of atrophy of the hippocampus and related structures has been revisited; the value, relation with pathology, and significance of CSF biomarkers are better known; and interpretation of data from amyloid PET imaging has improved, its correlation with pathology clarified, and new ligands have been introduced. The objectives of the proposed revision are to clarify, in the context of this consensus framework, how the criteria can be applied, maintaining the principle of a high specificity. Our aims are as follows: (1) to present a new diagnostic algorithm for typical AD; (2) to advance the diagnostic criteria for atypical AD; (3) to refine the diagnostic criteria for mixed AD; (4) to elaborate the criteria for the diagnosis of the preclinical states of AD; and (5) to differentiate the biomarkers of AD diagnosis from those of AD progression.
Section snippets
Conceptual advances of the new criteria
AD has traditionally been defined as a type of dementia, a notion brought into existence with the publication of criteria from the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer's Disease and Related Disorders Association (NINCDS–ADRDA) in 1984.3 Two major tenets of these criteria were as follows: (1) the clinical diagnosis of AD could only be designated as “probable” while the patient was alive and could not be made definitively until Alzheimer's pathology
Methods
The IWG recognised the limitations of the initial criteria and the need to take advantage of rapid progress in the field, and considered that the criteria for the diagnosis of AD might be improved in the light of a more comprehensive body of evidence than was available at their initial formulation in 2007. For this update, an extensive review of the literature was undertaken by BD and LCdS with key search themes (AD diagnosis, preclinical states, prodromal AD, atypical and mixed AD, CSF and
New evidence on tests to identify AD memory disorders
Memory disorders that manifest as free recall deficits occur in many brain diseases other than AD.28, 29, 30 A specific episodic memory disorder has been reported in AD, which is the manifestation of a hippocampal dysfunction4 and can be identified by tests that include list learning. Of these, the free and cued selective reminding test (FCSRT) was specifically recommended in the 2007 criteria because of two major advantages: it controls for a successful encoding (achieved by cued recall) and
The case for refining the diagnostic algorithm
In an estimated 6–14% of cases,115, 116, 117 the presentation of AD varies from the typical amnestic form. Patients with an atypical clinical presentation probably account for most of the 11% of AD cases with an atypical pathological distribution at autopsy.118 Each of these atypical forms of AD presents with a relative preservation of memory plus a recognisable (or characteristic) phenotype that might be accompanied by topographical evidence of brain damage (regional atrophy or hypometabolism)
The case for refining the diagnostic algorithm
The IWG initially defined mixed AD as the co-occurrence of Alzheimer's pathology with other pathologies that might contribute to the cognitive decline, such as normal pressure hydrocephalus, hippocampal sclerosis, and most often cerebrovascular disease or Lewy body disease.11 Mixed AD has been reported to represent at least 50% of all AD cases at autopsy, with a particularly high prevalence in people older than 80 years.136, 137 The recognition of mixed pathology in clinical diagnosis is
The case for new criteria for the diagnosis of preclinical states
The disappointing results of drugs targeting Aβ in recent clinical trials for patients with mild to moderately severe AD have engendered the belief that these therapies are being tested too late in the process of the disease and that earlier intervention is needed to ameliorate the course of AD.146, 147 In turn, interest has intensified in defining the preclinical states of AD through research projects on the natural history and trajectory of the disease, to design secondary preventive clinical
Refining the use of pathophysiological and topographical biomarkers
Alzheimer's pathology consists of brain amyloid deposition and neurofibrillary tangles, generally associated with synaptic loss and vascular amyloid deposits. Where they develop, these lesions induce functional deficits and neuronal death. Variations in the hierarchy and relationships between Aβ load, cerebral hypometabolism, and atrophy have been reported.158 However, these changes account for regional hypometabolism, atrophy of specific structures, and cognitive disorders in relation to the
Discussion
In this paper, we refine the IWG research diagnostic criteria for AD to provide a more simplified algorithm based on specific AD clinical phenotypes with in-vivo evidence of Alzheimer's pathology through either a molecular AD signature in CSF or positive amyloid imaging (figure). This simplified diagnostic algorithm reinforces our understanding of AD as a clinicobiological entity and allows the application of a single set of diagnostic criteria at any stage of the disease. We broaden the
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